Load packages
library(tidyverse)
library(gridExtra)
library(cowplot)
library(ggridges)
library(ggstance)
library(treeio)
library(ggtree)
library(tidytree)
Load and combine data
species <- read_csv("../data/species_data.csv") %>% select(-species)
data <- read_csv("../data/data.csv") %>%
left_join(species, by = c("species" = "species_formatted")) %>%
rename(label = species_latin)
data2 <- data %>% group_by(species, label) %>% summarise(n = sum(n))
fulltree <- read.nexus("../data/consensusTree_10kTrees_298Primates_V3.nex")
refs <- read_csv("../data/ref_nodes.csv")
# turn tree into tidy dataframe
tree2 <- as_tibble(fulltree)
tree3 <- tree2 %>%
left_join(data2) %>%
mutate(
hasN = ifelse(is.na(n), 0, .5),
hasN2 = ifelse(is.na(n), .1, .5)) %>%
left_join(refs) %>%
# # also merge w datasheet listing node, n for inner nodes
# left_join(Ns, by = "node") %>%
# mutate(n = coalesce(n.x, n.y)) %>%
# select(-n.x, -n.y) %>%
groupClade(c(493, 496, 429, 302, 408)) %>%
mutate(group = fct_recode(group, "2" = "1"))
Joining, by = "label"
Joining, by = "node"
# turn back into tree
tree4 <- as.treedata(tree3)
Circular tree of 298 primates
cols <- viridis::viridis(4, end = .9)
# base plot
p <- ggtree(tree4, aes(size = hasN, alpha = hasN2), layout = "circular") +
# root
geom_rootpoint(size = 1) +
# tips
geom_tippoint(aes(size = n), alpha = .5) +
geom_tiplab2(aes(alpha = hasN), offset = 2, size = 3) +
# tweak scales
scale_alpha_continuous(range = c(.3, 1)) +
scale_size_continuous(range = c(.5, 8)) +
# widen plotting area
xlim(NA, 100)
# highlight clades with background colors
p2 <- p +
geom_hilight(node = 493, fill = cols[1], alpha = .3) +
geom_hilight(node = 496, fill = cols[1], alpha = .3) +
geom_hilight(node = 429, fill = cols[2], alpha = .3) +
geom_hilight(node = 303, fill = cols[3], alpha = .3) +
geom_hilight(node = 408, fill = cols[4], alpha = .3) +
# plot tree again to be on top of the highlights
geom_tree() +
geom_rootpoint(size = 1)
# highlight clades with branch colors
p3 <- p +
aes(col = group) +
scale_color_manual(values = c("gray30", cols))
plots <- mget(c("p", "p2", "p3"))
grid.arrange(p, p2, p3, nrow = 1)

# png with 3x1
ggsave("../graphs/phylo_full.png", arrangeGrob(grobs = plots, nrow = 1),
width = 24, height = 8, scale = 2, dpi = 72)
Removed 287 rows containing missing values (geom_point_g_gtree).Removed 287 rows containing missing values (geom_point_g_gtree).Removed 287 rows containing missing values (geom_point_g_gtree).
# pdf with 1 per page
ggsave("../graphs/phylo_full.pdf", marrangeGrob(grobs = plots, nrow = 1, ncol = 1),
width = 8, height = 8, scale = 2, dpi = 72)
Removed 287 rows containing missing values (geom_point_g_gtree).Removed 287 rows containing missing values (geom_point_g_gtree).Removed 287 rows containing missing values (geom_point_g_gtree).
Sample size in detail
# subset tree to just those species who have sample sizes reported, i.e. those who were tested
to_drop <- tree3 %>% filter(is.na(n)) %>% pull(label)
tree5 <- drop.tip(tree4, to_drop)
# make NA when equal to d4$Mdn
d4 <- full_join(d4a, d4b) %>%
mutate(Mdn_site2 = ifelse(Mdn == Mdn_site2, NA, Mdn_site2))
Joining, by = c("label", "species")

ggsave("../graphs/phylo_ridge_site.png", width = 4, height = 3, scale = 2)
Session info
sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Mojave 10.14.5
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] tidytree_0.2.8 ggtree_1.16.6 treeio_1.8.2 ggstance_0.3.3 ggridges_0.5.1
[6] cowplot_1.0.0 gridExtra_2.3 forcats_0.4.0 stringr_1.4.0 dplyr_0.8.3
[11] purrr_0.3.2 readr_1.3.1 tidyr_1.0.0 tibble_2.1.3 ggplot2_3.2.1
[16] tidyverse_1.2.1
loaded via a namespace (and not attached):
[1] tidyselect_0.2.5 xfun_0.10 reshape2_1.4.3 haven_2.1.1 lattice_0.20-38
[6] colorspace_1.4-1 vctrs_0.2.0 generics_0.0.2 viridisLite_0.3.0 rlang_0.4.0
[11] pillar_1.4.2 glue_1.3.1 withr_2.1.2 modelr_0.1.5 readxl_1.3.1
[16] rvcheck_0.1.5 lifecycle_0.1.0 plyr_1.8.4 munsell_0.5.0 gtable_0.3.0
[21] cellranger_1.1.0 rvest_0.3.4 labeling_0.3 knitr_1.25 parallel_3.6.1
[26] broom_0.5.2 Rcpp_1.0.2 BiocManager_1.30.7 scales_1.0.0 backports_1.1.5
[31] jsonlite_1.6 hms_0.5.1 stringi_1.4.3 grid_3.6.1 cli_1.1.0
[36] tools_3.6.1 magrittr_1.5 lazyeval_0.2.2 crayon_1.3.4 ape_5.3
[41] pkgconfig_2.0.3 zeallot_0.1.0 xml2_1.2.2 lubridate_1.7.4 viridis_0.5.1
[46] assertthat_0.2.1 httr_1.4.1 rstudioapi_0.10 R6_2.4.0 nlme_3.1-141
[51] compiler_3.6.1
---
title: "Phylogenetic Tree"
output: 
  html_notebook:
    css: style.css
    theme: paper
---

Load packages

```{r, message=FALSE}
library(tidyverse)
library(gridExtra)
library(cowplot)
library(ggridges)
library(ggstance)
library(treeio)
library(ggtree)
library(tidytree)
```

Load and combine data

```{r, message=FALSE}
species <- read_csv("../data/species_data.csv") %>% select(-species)
data <- read_csv("../data/data.csv") %>% 
  left_join(species, by = c("species" = "species_formatted")) %>% 
  rename(label = species_latin)
data2 <- data %>% group_by(species, label) %>% summarise(n = sum(n))
fulltree <- read.nexus("../data/consensusTree_10kTrees_298Primates_V3.nex")
refs <- read_csv("../data/ref_nodes.csv")
```

```{r}
# turn tree into tidy dataframe
tree2 <- as_tibble(fulltree)

tree3 <- tree2 %>% 
  left_join(data2) %>% 
  mutate(
    hasN = ifelse(is.na(n), 0, .5),
    hasN2 = ifelse(is.na(n), .1, .5)) %>% 
  left_join(refs) %>% 
  # # also merge w datasheet listing node, n for inner nodes
  # left_join(Ns, by = "node") %>% 
  # mutate(n = coalesce(n.x, n.y)) %>% 
  # select(-n.x, -n.y) %>% 
  groupClade(c(493, 496, 429, 302, 408)) %>% 
  mutate(group = fct_recode(group, "2" = "1"))

# turn back into tree
tree4 <- as.treedata(tree3)
```

# Figure out nodes

This makes a rectangular and a circular tree with the node numbers displayed for reference (saved in the `graphs` folder).

```{r}
tree3.2 <- as.treedata(tree3)
```

```{r, fig.width=8, fig.height=20, eval=FALSE}
# display node numbers for reference
ggtree(tree3.2) +
  # tip labels
  geom_tippoint(aes(size = n), col = "seagreen", alpha = .5) +
  geom_tiplab(offset = 1, size = 3) +
  # node labels
  geom_text(aes(label = node, x = branch), size = 2, col = "blue", vjust = -.5) +
  expand_limits(x = 90) +
  # display timescale at the bottom
  theme_tree2()
```

```{r, eval=FALSE}
ggsave("../graphs/full_tree_nodes.pdf", width = 8, height = 20, scale = 2)
```

```{r, fig.width=8, fig.height=8, eval=FALSE}
ggtree(tree3.2, layout = "circular") +
  geom_tippoint(aes(size = n), col = "seagreen", alpha = .5) +
  geom_tiplab2(offset = 2, size = 3) +
  geom_text2(aes(label = node), size = 1.5, col = "blue") +
  xlim(NA, 100)
```

```{r, eval=FALSE}
ggsave("../graphs/full_tree_nodes_circular.pdf", width = 8, height = 8, scale = 2)
```

# Circular tree of 298 primates

```{r}
cols <- viridis::viridis(4, end = .9)
```

```{r}
# base plot
p <- ggtree(tree4, aes(size = hasN, alpha = hasN2), layout = "circular") +
  # root
  geom_rootpoint(size = 1) +
  # tips
  geom_tippoint(aes(size = n), alpha = .5) +
  geom_tiplab2(aes(alpha = hasN), offset = 2, size = 3) +
  # tweak scales
  scale_alpha_continuous(range = c(.3, 1)) +
  scale_size_continuous(range = c(.5, 8)) +
  # widen plotting area
  xlim(NA, 100)
```

```{r}
# highlight clades with background colors
p2 <- p + 
  geom_hilight(node = 493, fill = cols[1], alpha = .3) +
  geom_hilight(node = 496, fill = cols[1], alpha = .3) +
  geom_hilight(node = 429, fill = cols[2], alpha = .3) +
  geom_hilight(node = 303, fill = cols[3], alpha = .3) +
  geom_hilight(node = 408, fill = cols[4], alpha = .3) +
  # plot tree again to be on top of the highlights
  geom_tree() +
  geom_rootpoint(size = 1)
```

```{r}
# highlight clades with branch colors
p3 <- p + 
  aes(col = group) +
  scale_color_manual(values = c("gray30", cols))
```

```{r}
plots <- mget(c("p", "p2", "p3"))
```

```{r, fig.width=18, fig.height=6}
grid.arrange(p, p2, p3, nrow = 1)
```

```{r}
# png with 3x1
ggsave("../graphs/phylo_full.png", arrangeGrob(grobs = plots, nrow = 1), 
       width = 24, height = 8, scale = 2, dpi = 72)

# pdf with 1 per page
ggsave("../graphs/phylo_full.pdf", marrangeGrob(grobs = plots, nrow = 1, ncol = 1), 
       width = 8, height = 8, scale = 2, dpi = 72)
```

# Sample size in detail

```{r}
# subset tree to just those species who have sample sizes reported, i.e. those who were tested
to_drop <- tree3 %>% filter(is.na(n)) %>% pull(label)
tree5 <- drop.tip(tree4, to_drop)
```

```{r}
data3 <- data %>% 
  select(label, everything()) %>% 
  rename(num = n)

# species with more than X sites can get a density?
d3a <- data3 %>% group_by(species) %>% filter(n_distinct(site) >= 4)
d3b <- data3 %>% # setdiff(data3, d3a) ## <- do setdiff instead to NOT show points for densities
  group_by(species) %>% 
  # create variable num2 is NA if there's only one data point for a species
  # --> those species will only get the vertical crossbar
  mutate(flag = n_distinct(site) == 1) %>% 
  ungroup %>% 
  mutate(num2 = ifelse(flag, NA, num))

# for vertical crossbar = median
d4a <- data3 %>% 
  group_by(label, species) %>% 
  summarise(Mdn = median(num)) # totalN = sum(num), sitesN = n_distinct(site)

# for cross = median (sample size by species and site)
d4b <- data3 %>% 
  group_by(label, species, site) %>% 
  summarise(Mdn_site = median(num))%>% 
  group_by(label, species) %>% 
  summarise(Mdn_site2 = median(Mdn_site))

# make NA when equal to d4$Mdn
d4 <- full_join(d4a, d4b) %>% 
  mutate(Mdn_site2 = ifelse(Mdn == Mdn_site2, NA, Mdn_site2))

# for vertical line in ridge plot (grand median)
# + hacky way to make horizontal grid lines for right panel only
v <- tibble(reference = c(NA, median(data3$num)), .panel = c("Tree", "xSample size"))
h <- tibble(reference = c(NA, 1:Ntip(tree5)), .panel = c("Tree", rep("xSample size", Ntip(tree5))))

# for axis labels
ax <- tibble(lab = c("Distance", "Sample size"), x = c(67.5, max(data3$num)/2), y = -.3, 
             .panel = c("Tree", "xSample size"))
```

```{r, fig.width=4, fig.height=3}
# right-side viz depends on the number of sites per species:
# 1 site = vertical crossbar only
# 2+ sites = points + crossbar at median
# X+ sites = densities (currently, X = 4 just to illustrate)

# dirty hack: x in front of "Sample size" is to have that panel sort to the right (alphabetically) until I figure out why it doesn't just go by order. This cropped up as an issue when I added the dummy point for the x-axis expansion...

# LEFT FACET
q <- ggtree(tree5, aes(col = group)) +
  # this is a dummy point to expand the x scale
  # the typical ways weirdly also expand it for the sample size panel once that's added
  # geom_point(data = tibble(x = 135, y = 1, .panel = "Tree", group = NA)) +
  # tip labels
  geom_tippoint(aes(size = n), alpha = .5) +
  geom_tiplab(offset = 4, size = 3) +
  # tweak scales
  scale_color_manual(values = c("grey30", cols)) +
  scale_fill_manual(values = cols[4]) + # when all categories are taken: cols
  # display timescale at the bottom
  theme_tree2() +
  xlim_tree(135) +
  # add axis labels
  geom_text(data = ax, aes(label = lab), col = "black") +
  scale_y_continuous(limits = c(1, Ntip(tree5)), oob = function(x, ...) x) +
  coord_cartesian(clip = "off") +
  # add reference lines (these will show up on right panel of facet_plot only)
  geom_hline(data = h, aes(yintercept = reference), lwd = .2, col = "grey", alpha = .5) +
  geom_vline(data = v, aes(xintercept = reference), lwd = 1.5, col = "grey", alpha = .3) +
  # remove facet strips
  # or element_text(size = 14)
  theme(strip.text = element_blank(), strip.background = element_blank(),
        plot.margin = unit(c(.5, .5, 1.2, .5), "cm"))

# ADD RIGHT FACET
q %>% 
  # densities for species with enough sites
  facet_plot("xSample size", d3a, geom_density_ridges, aes(x = num, group = label, fill = group), 
             alpha = .5, lwd = .3, position = position_nudge(y = .1)) %>% 
  # vertical crossbar for Mdn
  facet_plot("xSample size", d4, geom_crossbarh, aes(x = Mdn, xmin = Mdn, xmax = Mdn, group = label, 
             col = group), alpha = .5, width = .3) %>%
  # x for Mdn_site
  facet_plot("xSample size", d4, geom_point, aes(x = Mdn_site2, group = label), shape = 4, size = 2, stroke = 1.5, alpha = .8) %>%
  # vertical mark for individual sites
  facet_plot("xSample size", d3b, geom_point, aes(x = num2, group = label), shape = "|", size = 3) #+
```

```{r}
ggsave("../graphs/phylo_ridge_site.png", width = 4, height = 3, scale = 2)
```

# Session info

```{r}
sessionInfo()
```

